Modeling potential invasion range of alien invasive species, Hyptis suaveolens (L.) Poit. in India: Comparison of MaxEnt and GARP

Padalia, Hitendra; Srivastava, Vivek; Kushwaha, S. P. S.

doi:10.1016/j.ecoinf.2014.04.002

Cited by 188 publications

(108 citation statements)

References 30 publications

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“…), it can be used to compare the performances of MaxEnt and GARP models (Padalia et al. ). By giving different weight to GARP and Maxent, using the function of grid calculator in ArcGIS, the scope of the high suitability can be reduced; the area where is high suitable or low suitable is more obvious.…”

Section: Discussionmentioning

confidence: 99%

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The distribution of Athetis lepigone and prediction of its potential distribution based on GARP and MaxEnt

Wang

Li³

et al. 2016

J Applied Entomology

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Athetis lepigone (Möschler) is a new agronomic pest which has caused serious damages to summer maize in China. In order to effectively monitor it, it is necessary to carry‐out a worldwide investigation on its potential geographical distribution. In this study, we give two ecological niche models, Genetic Algorithm for Rule‐set Production and Maximum Entropy (MaxEnt), to predict the potential geographical distribution of A. lepigone. The results indicate that the suitable areas for A. lepigone are mainly in China (Beijing, Tianjin, central and southern Hebei, northern Jiangsu, Shandong, most of Henan, northern Anhui, central and southern Shanxi, central and southern Shaanxi, small parts of north‐west in Hubei, eastern Gansu, parts of Ningxia, western of Xinjiang and Dandong, and Liaoning) and other Asian countries (South Korea, North Korea and Japan). Parts of Europe (south‐western Russia, Ukraine, Moldova, Romania, Hungary, Bulgaria, Slovenia, and Croatia, Bosnia and Herzegovina, Serbia, parts of Austria, western Poland, the Czech Republic, Germany, northern Italy, Denmark, western Lithuania, Latvia, Estonia, southern Finland and Sweden) are also highly suitable for A. lepigone. In addition, in the states of the USA including Michigan, New York, Chicago, Missouri, Ohio, Illinois and Indiana are also favourable for its occurrence although till now no reports about of this species has been recorded. A jackknife test in MaxEnt showed that the mean temperature of the driest quarter was the most important environmental variable affecting the distribution of this pest.

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Section: Discussionmentioning

confidence: 99%

“…In addition, they are a very important accuracy check to ensure that the relationships, on which the model results are based, are realistic (Padalia et al. ). After being analysed, the response curves explain the patterns observed in the MaxEnt output.…”

Section: Methodsmentioning

confidence: 99%

The distribution of Athetis lepigone and prediction of its potential distribution based on GARP and MaxEnt

Wang

Li³

et al. 2016

J Applied Entomology

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“…Further, 1,000 iterations were carried out to allow for convergence, thereby reducing the chance of over or underprediction (Frake, ). Variable importance estimation was carried out using both the heuristic test and the jackknife procedure; the latter helps to evaluate the independent contribution of variables to the habitat suitability model (Padalia, Srivastava, & Kushwaha, ). It should be noted that 75% of the training data were used for model training and 25% data were employed for model testing (Lahoz‐Monfort et al., ).…”

Section: Methodsmentioning

confidence: 99%

Remote sensing‐based landscape indicators for the evaluation of threatened‐bird habitats in a tropical forest

Singh

Tokola

Hou

et al. 2017

Ecology and Evolution

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Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space‐borne optical (Landsat), ALOS‐PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest—agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature (IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR‐derived forest structure and Landsat‐derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the avian species. This work also provides insight that retention of forest patches, including degraded and isolated forest patches in addition to large contiguous forest patches, can facilitate bird species retention within tropical agricultural landscapes. It also demonstrates the effective use of RS data in distinguishing between forests that have undergone varying levels of degradation and identifying the habitat preferences of different bird species. Practical conservation management planning endeavors can use such data for both landscape scale monitoring and habitat mapping.

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“…However, national‐ and global‐scale data can be obtained by integrating multiple datasets collected and managed by different researchers (Figure ). For example, García‐Roselló et al () have predicted global distribution patterns of marine fish and Padalia et al () have predicted the potential invasion range of alien invasive species in India. Together with my colleagues, I have studied the relationships between the distribution of threatened plants and agricultural land use in Japan (Osawa, Kamauchi, Hosoya, & Ito, ; Osawa, Kohyama, & Mitsuhashi, ; Osawa, Kohyama, & Mitsuhashi, ; Osawa & Mitsuhashi, ).…”

Section: Ecological Research Based On Existing Datamentioning

confidence: 99%

Perspectives on biodiversity informatics for ecology

Osawa

2019

Ecological Research

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Biodiversity informatics is the application of informatics techniques to ecology and biodiversity sciences. The premise is utilizing natural history collections/data, such as specimens and biodiversity observations, with information and communication technology. During the past two decades, biodiversity informatics has improved dramatically and has been applied increasingly in ecology science. In this paper, I review biodiversity informatics for ecology with a particular focus on the treatment of data. First, I discuss the traditional perspective of data collection and its usage in the ecological community. Then, I provide an overview of the trajectory of changing perspectives of data treatment relative to developing biodiversity informatics (i.e., the infiltration of the data reuse and sharing concepts). Specifically, I discuss the significance of data reuse, which offers numerous benefits for research, and data sharing with their supporting mechanisms and case studies. Finally, I discuss potential future developments in biodiversity informatics relative to the field of ecology.

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Modeling potential invasion range of alien invasive species, Hyptis suaveolens (L.) Poit. in India: Comparison of MaxEnt and GARP

Cited by 188 publications

References 30 publications

The distribution of Athetis lepigone and prediction of its potential distribution based on GARP and MaxEnt

The distribution of Athetis lepigone and prediction of its potential distribution based on GARP and MaxEnt

Remote sensing‐based landscape indicators for the evaluation of threatened‐bird habitats in a tropical forest

Perspectives on biodiversity informatics for ecology

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